Dataset Information

Gout and the risk of advanced chronic kidney disease in the UK health system: a national cohort study.

ABSTRACT:

Objective

Evaluate the association between gout and risk of advanced chronic kidney disease (CKD).

Design

Retrospective matched cohort study.

Setting

UK Clinical Practice Research Datalink.

Participants

The analysis included data for 68?897 patients with gout and 554?964 matched patients without gout. Patients were aged ?18 years, registered at UK practices, had ?12 months of clinical data and had data linked with Hospital Episode Statistics. Patients were excluded for history of advanced CKD, juvenile gout, cancer, HIV, tumour lysis syndrome, Lesch-Nyhan syndrome or familial Mediterranean fever.

Primary and secondary outcome measures

Advanced CKD was defined as first occurrence of: (1) dialysis, kidney transplant, diagnosis of end-stage kidney disease (ESKD) or stage 5 CKD (diagnostic codes in Read system or International Classification of Diseases, Tenth Revision); (2) estimated glomerular filtration rate (eGFR) <10 mL/min/1.73 m²; (3) doubling of serum creatinine from baseline and (4) death associated with CKD.

Results

Advanced CKD incidence was higher for patients with gout (8.54 per 1000 patient-years; 95% CI 8.26 to 8.83) versus without gout (4.08; 95%?CI 4.00 to 4.16). Gout was associated with higher advanced CKD risk in both unadjusted analysis (HR, 2.00; 95%?CI 1.92 to 2.07) and after adjustment (HR, 1.29; 95%?CI 1.23 to 1.35). Association was strongest for ESKD (HR, 2.13; 95%?CI 1.73 to 2.61) and was present for eGFR <10?mL/min/1.73?m² (HR, 1.45; 95%?CI 1.30 to 1.61) and serum creatinine doubling (HR, 1.13; 95%?CI 1.08 to 1.19) but not CKD-associated death (HR, 1.14; 95%?CI 0.99 to 1.31). Association of gout with advanced CKD was replicated in propensity-score matched analysis (HR, 1.23; 95%?CI 1.17 to 1.29) and analysis limited to patients with incident gout (HR, 1.28; 95%?CI 1.22 to 1.35).

Conclusions

Gout is associated with elevated risk of CKD progression. Future studies should investigate whether controlling gout is protective and reduces CKD risk.

SUBMITTER: Stack AG

PROVIDER: S-EPMC6720233 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Gout and the risk of advanced chronic kidney disease in the UK health system: a national cohort study.

Stack Austin G AG Johnson Michelle Elizabeth ME Blak Betina B Klein Alyssa A Carpenter Lewis L Morlock Robert R Maguire Andrew R AR Parsons Victoria L VL

BMJ open 20190828 8

<h4>Objective</h4>Evaluate the association between gout and risk of advanced chronic kidney disease (CKD).<h4>Design</h4>Retrospective matched cohort study.<h4>Setting</h4>UK Clinical Practice Research Datalink.<h4>Participants</h4>The analysis included data for 68 897 patients with gout and 554 964 matched patients without gout. Patients were aged ≥18 years, registered at UK practices, had ≥12 months of clinical data and had data linked with Hospital Episode Statistics. Patients were excluded f ...[more]

PMID: 31462487

Similar Datasets

Project description:BACKGROUND:Gout is a common inflammatory arthritis associated with adverse clinical outcomes. Under treatment is common in the general population. The aim of this study was to determine the prevalence of gout and its treatment among patients with chronic kidney disease (CKD). METHODS:We conducted a multi-centre cross sectional study of patients (n = 522) who attended specialist nephrology clinics in Ireland. Standardized data collection tool recorded clinical characteristics and medication use at clinic visits and kidney function was assessed with standardised creatinine measurements and Estimated Glomerular Filtration Rate (eGFR). The prevalence of gout and the corresponding use of urate lowering therapies (ULT) were determined. Multivariate logistic regression explored correlates of gout expressed as Odds Ratios (OR) and 95% Confidence Intervals (CI) adjusting for demographic and clinical characteristics. RESULTS:Overall prevalence of gout was 16.6% and increased significantly from 7.5% in Stage 1-2 CKD to 22.8% in stage 4-5 CKD, P< 0.005. Prevalence increased with age (P < 0.005) and was higher in men than women (19.1% versus 10.3% P< 0.005). Overall, 67.9% of gout patients with CKD were treated with ULT, and the percentage increased with advancing stage of CKD from 55.6% in Stage 1-2 to 77.4% in Stage 4-5, P<0.005. Multivariable modelling identified men (vs women), OR, 1.95 (0.95-4.03), serum albumin, OR 1.09 (1.02-1.16) per 1 g/L lower, poorer kidney function, OR 1.11 (1.01-1.22) per 5 ml/min/1.73m2 lower, and rising parathyroid hormone levels, OR 1.38 (1.08-1.77) per 50 pg/ml higher as disease correlates. CONCLUSIONS:Gout is common in CKD and increases with worsening kidney function in the Irish health system. Over two thirds of patients with gout were receiving ULT, increasing to 77% of patients with advanced CKD. Greater awareness of gout in CKD, its treatment and the effectiveness of treatment strategies should be vigorously monitored to improve patient outcomes.

Project description:BackgroundChronic Kidney Disease (CKD) is a major non-communicable chronic disease that is associated with adverse clinical and economic outcomes. Passive surveillance systems are likely to improve efforts for prevention of chronic kidney disease (CKD) and inform national service planning. This study was conducted to determine the overall prevalence of CKD in the Irish health system, assess period trends and explore patterns of variation as part of a novel surveillance initiative.MethodsWe identified 207, 336 adult patients, age 18 and over, with serum creatinine measurements recorded from a provincial database between 2005-2011 in the Northwest of Ireland. Estimated glomerular filtration rates (eGFR) were determined using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation from standardized creatinine measurements and the presence of CKD was defined as eGFR<60 ml/min per 1.73 m2. Age and sex-specific prevalence estimates were determined for each group while generalized estimating equations (GEE) and multivariable logistic regression were used to explore associations using adjusted odds ratios (AOR) and 95% confidence intervals (95% CI).ResultsThe prevalence of CKD in the health system was 11.8% (95% CI 11.8-12.1); 10.9% in men (10.7-11.1) and 12.6% in women (12.4-12.8). This corresponded to a detection rate of 4.5% (5.1% in women and 3.9% in men). The prevalence of CKD was significantly higher in women than in men (12.6% versus 10.9%, P<0.001), older age groups, and among patients with a history of Acute Kidney Injury (AKI) than without (45.2% versus 10.7%, P<0.0001). Multivariable analysis identified advancing age, female gender, location of medical supervision, county of residence, and AKI as significant determinants of prevalence.ConclusionThe prevalence of CKD in the Irish health system is 11.8% corresponding to a detection rate of 4.5% in the general population. Demographic, geographic factors and acute kidney injury episodes are important determinants of disease burden. Passive surveillance of CKD is both feasible and desirable within the Irish health system, and offers huge opportunities for targeted prevention programmes and improved clinical outcomes.

Project description:To evaluate the association between incidence of any kidney cancer and type 2 diabetes mellitus.A random sample of 1,000,000 subjects covered by the National Health Insurance was recruited. A total of 998728 people (115655 diabetes and 883073 non-diabetes) without kidney cancer at recruitment were followed from 2003 to 2005. The cumulative incidence of kidney cancer from 2003 to 2005 in diabetic patients and non-diabetic people in all ages and in age <40, 40-64, 65-74 and ? 75 years were calculated in the diabetic patients and the non-diabetic people, respectively. Logistic regression was used to estimate the odds ratios comparing diabetic patients to non-diabetic people in the respective age groups. Multivariable-adjusted odds ratios for kidney cancer with regards to diabetes status and diabetes duration (as a continuous variable or categorized into subgroups of non-diabetes, diabetes duration <1 year, 1-2.9 years, 3-4.9 years and ? 5 years) were estimated after multivariable adjustment. The multivariable-adjusted odds ratios for all baseline variables were also estimated for diabetic patients and non-diabetic people, respectively.The 3-year cumulative incidence of kidney cancer in the diabetic patients and the non-diabetic people was 166.9 and 33.1 per 100,000 person-years, respectively. The incidence increased with regards to increasing age in both the diabetic patients and the non-diabetic people, but a higher risk of kidney cancer for the diabetic patients compared to the non-diabetic people was consistently observed in different age groups. After multivariable adjustment, the odds ratio for diabetic patients versus non-diabetic people was 1.7 (95% confidence interval: 1.3-2.1, P<0.01). While compared to the non-diabetic people, the odds ratio (95% confidence interval) for diabetes duration <1, 1-2.9 years, 3-4.9 years and ? 5 years was 1.5 (0.8-2.7), 1.6 (1.0-2.4), 1.6 (1.1-2.4) and 1.7 (1.3-2.3), respectively (P-trend <0.01). Analyses conducted in the diabetic patients and the non-diabetic people, respectively, consistently showed age, nephropathy and end-stage renal disease as significant risk factors of kidney cancer. Additionally, living in metropolitan Taipei region might also be associated with a higher risk of kidney cancer in the non-diabetic people, indicating a potential link between kidney cancer and some factors related to urbanization.Patients with type 2 diabetes mellitus have a significantly higher risk of kidney cancer.

Dataset Information

Gout and the risk of advanced chronic kidney disease in the UK health system: a national cohort study.

Objective

Design

Setting

Participants

Primary and secondary outcome measures

Results

Conclusions

Publications

Gout and the risk of advanced chronic kidney disease in the UK health system: a national cohort study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets